The present invention relates generally to imaging. More particularly, the present invention pertains to the use of a nonlinear post-beamforming filter in ultrasound imaging.
Many conventional ultrasound scanners create two-dimensional images of tissue located in a region of interest in which brightness of a pixel in the image is based on intensity of echo return following the provision of wave energy directed towards the region of interest. Such images may be formed from a combination of fundamental and harmonic signal components, the former being direct echoes of the transmitted pulse, and the latter being generated in a nonlinear medium, such as tissue, from finite amplitude ultrasound propagation. As is known, many times, ultrasound images can be improved by suppressing the fundamental and emphasizing the harmonic signal components.
Propagation of ultrasound wave energy in biological tissues is known to be nonlinear, giving rise to generation of harmonics. In harmonic imaging, energy is transmitted at a fundamental frequency, f0, and, for example, an image may be formed using energy at the second harmonic, 2f0.
Further, generally, in many instances, ultrasound contrast agents have been used for ultrasound imaging, e.g., imaged by using standard echo imaging or second harmonic imaging. Harmonic imaging is usually preferred over standard echo imaging when contrast agents are present because, for example, the harmonic signal components returned from contrast agents is generally much larger than that from surrounding tissue. Furthermore, for example, harmonic imaging provides a more desirable contrast between blood and tissue, and is able to reduce artifacts due to phase aberrations in the body. However, since harmonic imaging still receives signal from tissue, the specificity between contrast agent and tissue is still limited.
The diagnostic applications of ultrasound imaging have expanded enormously in recent years. Various improvements of ultrasound imaging as a diagnostic technique for medical decision-making have been established. Some of these improvements were with regard to ultrasound hardware/equipment, such as phased array transducers. Other improvements have included the introduction of signal processing algorithms that produced image enhancements, or more even, new forms of imaging such as color flow Doppler imaging.
Various methods to exploit the nonlinear nature of ultrasonic propagation in tissue media are being used in an attempt to provide improved imaging techniques for enhancing ultrasonic imaging, with or without the use of contrast agents. For example, second harmonic imaging improves the image contrast by significantly reducing the acoustic clutter from intervening tissue layers. This is particular advantageous for difficult to image patients.
The simplest implementation of second harmonic imaging is the use of a post-beamforming bandpass filter to separate the second harmonic from the fundamental. The assumption is that if the transmitted imaging pulse is carefully designed to have frequency components in the band f0xe2x88x92B/2 to f0+B/2, then second-order linear effects produce new frequency components in the band 2f0xe2x88x92B to 2f0+B. However, this technique puts significant constraints on the transducer bandwidth, f0xe2x88x92B/2 to 2f0+B. Significant signal loss occurs since most transducers are not capable of supporting such a bandwidth.
Various enhancements have been made to this simple implementation of second harmonic imaging. For example, a pulse inversion technique has been proposed and described in Simpson et al., xe2x80x9cPulse Inversion Doppler: A New Method for Detecting Nonlinear Echoes from Microbubble Contrast Agents,xe2x80x9d IEEE Trans. On Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 46, No. 2, (1999), and also M. A. Averkiou, xe2x80x9cTissue Harmonic Imaging,xe2x80x9d 2000 IEEE Ultrasonics Symposium, Vol. 2, pp. 1563-1572 (2000).
Further, other ultrasonic imaging techniques are moving rapidly towards employing post-beamforming filters combined with nonlinear imaging modes. For example, in U.S. Pat. No. 6,290,647 B1 to Krishnan, entitled, xe2x80x9cContrast Agent Imaging with Subharmonic and Harmonic Signals in Diagnostic Medical Ultrasound,xe2x80x9d issued Sep. 18, 2001, a combination of the results of linear filtering of harmonic and subharmonic components are used to produce improved contrast imaging. Further, another ultrasound imaging approach is described in an article by Haider, B. and Chiao, R. Y., entitled xe2x80x9cHigher Order Nonlinear Ultrasonic Imaging,xe2x80x9d 1999 IEEE Ultrasonics Symposium, Vol. 2, pp 1527-1531 (1999).
However, such techniques and enhancements are not without their own limitations. For example, the approach of Haider and Chiao performs nonlinear imaging by recognizing the nonlinear behavior of the system as a static polynomial-type nonlinearity. It does not recognize or take into consideration the dynamic behavior of the system.
Further, the approach by, for example, Haider and Chiao, and also the pulse inversion techniques, require the use of multiple transmits in the same direction for estimating coefficients of harmonic bases functions of the models utilized. When relying on the use of multiple transmissions, movement of the imaged region results in undesirable degradation of the image produced by the ultrasound system.
The present invention provides for ultrasound imaging through the use of a dynamic nonlinear post-beamforming filter (e.g., based on a pth-order Volterra model) capable of separating the linear and nonlinear components of image data, e.g., extracting the nonlinear components of the image data. The techniques described are applicable to both tissue and contrast agent nonlinearity, but are clearly not limited thereto. A system identification algorithm for deriving the filter coefficients is also provided. The filter-based approach is capable of extracting a broad band of frequencies that allow for contrast enhancement while preserving image detail. True nonlinear interaction between these frequency components is accounted for with use of a pth-order Volterra filter.
A method for use in ultrasound imaging of matter in a region according to the present invention includes providing wave energy into the region. The wave energy has a pulse spectrum centered at a fundamental frequency. Wave energy returned from the region is transduced to form a set of receive signals and the set of receive signals are beamformed to provide beamformed data representative of at least a portion of the region. The linear and non-linear components of the beamformed data are separated based on a pth-order Volterra model, where p is equal to or greater than 2. At least the non-linear components of the beamformed data are processed for use in forming an image.
In one embodiment of the method, separating the linear and non-linear components of the beamformed data based on a pth-order Volterra model includes applying a second-order Volterra filter to the beamformed data. The second-order Volterra filter is preferably defined by coefficients for a linear filter kernel and a quadratic non-linear filter kernel.
In another embodiment of the method, separating the linear and non-linear components of the beamformed data based on a pth-order Volterra model includes applying a pth-order Volterra filter to the beamformed data, wherein the pth-order Volterra filter is defined by coefficients for a linear filter kernel and one or more non-linear filter kernels of the pth-order Volterra filter. Further, the coefficients for the pth-order Volterra filter are determined using the transduced wave energy returned from at least a portion of the region in response to a single pulse of wave energy.
In another embodiment of the method, processing at least the non-linear components of the beamformed data for use in forming an image includes comparing or compounding at least a portion of the non-linear components to at least a portion of the linear components for use in characterization of the matter in the region.
A system for use in ultrasound imaging of matter in a region according to the present invention includes an ultrasound transducer array having a plurality of transducer elements and pulse controller circuitry coupled to the ultrasound transducer array operable in a transmit mode to provide wave energy into the region. The wave energy has a pulse spectrum centered at a fundamental frequency. Further, the ultrasound transducer array is operable in a receiving mode to transduce wave energy returned from the region to form a set of receive signals. Further, the system includes a beamformer operable on the set of receive signals to provide beamformed data representative of at least a portion of the region and filter circuitry operable on the beamformed data to separate the linear and non-linear components of the beamformed data based on a pth-order Volterra model, where p is equal to or greater than 2. A processing apparatus is also provided that is operable to use at least non-linear components of the beamformed data in formation of an image.
In one embodiment of the system, the filter circuitry includes a second-order Volterra filter. Preferably, the second-order Volterra filter is defined by coefficients for a linear filter kernel and a quadratic non-linear filter kernel of the second-order Volterra filter.
Another method for use in imaging a region according to the present invention includes recognizing image data representative of a region (e.g., recognizing beamformed data resulting from transduced wave energy returned from the region in response to wave energy provided to the region). The image data has linear and non-linear components. The linear and non-linear components of the image data are separated based on a pth-order Volterra model, where p is equal to or greater than 2. At least the non-linear components of the image data are processed for use in forming an image.
Another system for use in imaging of matter in a region according to the present invention includes processing components for recognizing image data representative of a region, wherein the image data has linear and non-linear components. Further, the system includes filter components operable on the image data to separate the linear and non-linear components of the image data based on a pth-order Volterra model, where p is equal to or greater than 2. The processing components of the system may also provide at least the non-linear components of the image data for use in forming an image.
Yet another method for use in ultrasound imaging of matter in a region according to the present invention is described. The method includes providing wave energy into the region, wherein the wave energy has a pulse spectrum centered at a fundamental frequency. The wave energy returned from the region in response to a single pulse of wave energy is transduced to form a set of receive signals. The set of receive signals is beamformed to provide beamformed data representative of at least a portion of the region. Coefficients for a linear filter kernel and one or more non-linear filter kernels of a pth-order Volterra filter bank are determined using the beamformed data, where p is equal to or greater than 2. The linear filter kernel and one or more non-linear filter kernels are applied to the beamformed data and at least the beamformed data filtered by one or more of the non-linear filter kernels is processed for use in forming an image.
In one embodiment of the method, applying the linear filter kernel and one or more non-linear filter kernels to the beamformed data comprises applying the linear filter kernel and a quadratic non-linear filter kernel to the beamformed data based on a second-order Volterra model.
In another embodiment of the method, determining coefficients for a linear filter kernel and one or more non-linear filter kernels includes processing the beamformed data to provide at least one echographic image wherein the matter in the region can be perceived by a user, selecting at least a segment of the beamformed data from a contrast portion of the region where the matter is perceived, selecting at least a segment of the beamformed data from a normal portion of the region where the matter is not perceived, forming a linear system of equations based on the pth-order Volterra model, and providing a least squares solution to the linear system of equations to provide the at least one set of coefficients for a pth-order Volterra filter.
Further, the method may include providing regularization of the least squares solution. Such regularization may be provided, for example, by using single parameter and rank regularization guided by at least mean square error criterion and/or using single parameter and rank regularization guided by at least contrast to normal tissue ratio.